Ricci Curvature of the Internet Topology

Analysis of Internet topologies has shown that the Internet topology has negative curvature, measured by Gromov's "thin triangle condition", which is tightly related to core congestion and route reliability. In this work we analyze the discrete Ricci curvature of the Internet, defined by Ollivier, Lin, etc. Ricci curvature measures whether local distances diverge or converge. It is a more local measure which allows us to understand the distribution of curvatures in the network. We show by various Internet data sets that the distribution of Ricci cuvature is spread out, suggesting the network topology to be non-homogenous. We also show that the Ricci curvature has interesting connections to both local measures such as node degree and clustering coefficient, global measures such as betweenness centrality and network connectivity, as well as auxilary attributes such as geographical distances. These observations add to the richness of geometric structures in complex network theory.Comment: 9 pages, 16 figures. To be appear on INFOCOM 201

Three-Phase Detection and Classification for Android Malware Based on Common Behaviors

Android is one of the most popular operating systems used in mobile devices. Its popularity also renders it a common target for attackers. We propose an efficient and accurate three-phase behavior-based approach for detecting and classifying malicious Android applications. In the proposed approach, the first two phases detect a malicious application and the final phase classifies the detected malware. The first phase quickly filters out benign applications based on requested permissions and the remaining samples are passed to the slower second phase, which detects malicious applications based on system call sequences. The final phase classifies malware into known or unknown types based on behavioral or permission similarities. Our contributions are three-fold: First, we propose a self-contained approach for Android malware identification and classification. Second, we show that permission requests from an Application are beneficial to benign application filtering. Third, we show that system call sequences generated from an application running inside a virtual machine can be used for malware detection. The experiment results indicate that the multi-phase approach is more accurate than the single-phase approach. The proposed approach registered true positive and false positive rates of 97% and 3%, respectively. In addition, more than 98% of the samples were correctly classified into known or unknown types of malware based on permission similarities.We believe that our findings shed some lights on future development of malware detection and classification

Propofol Inhibits Lipopolysaccharide-Induced Tumor Necrosis Factor-Alpha Expression and Myocardial Depression through Decreasing the Generation of Superoxide Anion in Cardiomyocytes

TNF-α has been shown to be a major factor responsible for myocardial depression in sepsis. The aim of this study was to investigate the effect of an anesthetic, propofol, on TNF-α expression in cardiomyocytes treated with LPS both in vivo and in vitro. In cultured cardiomyocytes, compared with control group, propofol significantly reduced protein expression of gp91phox and phosphorylation of extracellular regulated protein kinases 1/2 (ERK1/2) and p38 MAPK, which associates with reduced TNF-α production. In in vivo mice studies, propofol significantly improved myocardial depression and increased survival rate of mice after LPS treatment or during endotoxemia, which associates with reduced myocardial TNF-α production, gp91phox, ERK1/2, and p38 MAPK. It is concluded that propofol abrogates LPS-induced TNF-α production and alleviates cardiac depression through gp91phox/ERK1/2 or p38 MAPK signal pathway. These findings have great clinical importance in the application of propofol for patients enduring sepsis

Transcriptomic comparison of the self-pollinated and cross-pollinated flowers of Erigeron breviscapus to analyze candidate self-incompatibility-associated genes

Table S1. Functional annotation of E.breviscapus transcriptome. (XLSX 4281 kb